NETWORK MANAGEMENT
Figure 4 shows the daily traffic profile of a major operator, where the traffic in peak hours can be 10 times higher than the one in off-peak periods. Realizing the potential in these slow traffic variations, vendors and operators have recently started to bundle traffic of certain transceivers, and switch others off in order to save energy. Beyond these basic techniques, self-organizing networks can be exploited to adapt the network topology to slow traffic variations. Furthermore, highly dynamic load variations should be addressed by energy efficient radio resource management strategies. Energy efficient adaptation to the daily and spatial variation of the traffic demand requires specific network management functionalities. The state-of-the-art solution is to simply reduce the number of active network elements when the traffic demand decreases however, once different energy efficient deployment scenarios are available for different traffic situations, new horizons open for network management. That is, network management can provide a seamless transition from one network configuration and topology setup to another, according to actual traffic demands, considering both slowly changing daily load patterns, as well as highly dynamic traffic fluctuations. The transition process from one network setup to another needs the reconfiguration of particular resources, or the coordinated reconfiguration of groups of resources, or even of the whole network. When traffic demand decreases, the transition process may include, e.g., switching off particular micro-/pico-cells, transferring a sectorized base station to an omnidirectional one, or increasing cell coverage by adapting the antenna tilt. When traffic demand increases, the transition process may include, e.g., switching between various MIMO functionalities, or directing adaptive antenna arrays towards traffic hotspots. Beyond the analysis of the above options, other issues are at stake, like developing new network management concepts for dynamic reconfiguration of mobile networks, including self-optimization, self-configuration and standbyoperation. When comparing different radio access technologies, one can find that some are more energy efficient for certain types of services than others. In order to take advantage of the coexistence of different radio access technologies, new network management functions are needed to control a common resource pool. That is, radio resource management has to involve cooperative scheduling, interference coordination, and joint power and radio resource control. There is a need to investigate how to define these management functionalities to leverage the capabilities of the different technologies, and to employ multi-radio access networks in a coordinated fashion for energy savings.